AI – what artificial intelligence is and is not

All the facts about AI you need to know for business and digital experiences.

The past few years have provided an endless barrage of articles and blogs talking about the importance and proliferance of artificial intelligence, and how it’s going to “disrupt” your industry. But what are the facts about AI? Do your organisation need it?

What is AI?

“Intelligence” is usually defined as the faculty of reasoning and integration of knowledge—i.e. connecting the dots. So “artificial intelligence” must mean a human-made interface with the power to reason and integrate knowledge.

However, it turns out that nobody can seem to agree what AI really entails, but we think an AI must demonstrate at least some of the following behaviors associated with human intelligence: planning, learning, reasoning, problem solving, knowledge representation, perception, motion, manipulation and, to a lesser extent, social intelligence, and creativity.

Machine learning: A computer system’s ability to improve performance with exposure to information, but without the need to follow explicit programming instructions. In machine learning the system automatically discovers patterns and attempts to make estimates.

Robotics: A robot might be a familiar concept to anyone, but could you describe it? In robotics scientist integrate artificial perception and automatised planning with actuators, thus creating the walking and talking entities we both fear and love.

Self-driving cars: Automated cars also combine so-called “computer vision”, or artificial perception, with predictive behaviour—this time in terms of steering, braking, and acceleration. But the fancy tech in cars don’t stop there: cars recognise e.g. the shape of raindrops on the windshield to activate the windshield wiper automatically.

Image recognition: This AI tech involves a computer system and the ability to recognise patterns, and then integrating similar patterns into the same group—just like we humans do, only we do it better (as of yet). Examples include Google Photos and tolls that read your licence plate.

Natural language processing: We have all laughed at the literal interpretations of computer systems, but this AI tech attempts to utilise context to identify a text’s genre, sentence structures, grammar, people mentioned, etc.

Speech recognition: Services like Amazon Alexa and Google Assistant wouldn’t work without speech recognition, which is an AI tech concerning itself with much of the same as natural language processing. Speech recognition additionally uses acoustics and predictive patterns for what sounds usually come after one another in a given language.

Personalisation: Personalised experiences on websites and apps aren’t necessarily artificial intelligence, but tailored recommendations can indeed be handled by an automated process. If you fit into a given demographic and have done certain actions, the AI behind the personalisation system might just try to figure out itself what tailored content to show just to you.

As a side note: An AI should not only recognise, but should also _do_ something with its gathered information. Sensors in your office can recognise shadows or movements, but that doesn’t make them artificial intelligence. If the sensors had recognised you as a person freezing, for instance, and then turned up the heat, then we are talking.

What AI is not

There is no rabbit in the hat when it comes to artificial intelligence. AI is not some magic that will solve anything for you and your digital experiences—just forget the notion. You can’t hire a robot to do all your tasks super-fast, you still need humans and will always do.

AI is first and foremost technology that can automatise lesser tasks, like finding a document faster for you. Also, contrary to what the doomsday preachers say, AI is not remotely close to human intelligence or concept-formation as we speak. AI can only do what is instructed within a given field

AI will not conquer the world. People might worry about losing their work to more effective robots and AI processes, but remember this: People worried about the same thing when the wheel was invented, when the first factories and gears arrived, when the assembly line arrived, and when computers first arrived. The results each time has been _more_ wealth and _more_ jobs. Don’t stay awake at night over AI.

Do digital experiences need AI?

How is artificial intelligence relevant to digital experiences and CMS? We have mentioned some of it already, but here goes:

Personalisation: Yes, this again. Making digital experiences personalised is almost a self-evident given in driving higher conversions. If an AI could recognise you and what you like, and then proceed to deliver exactly what you would like to see, that would be AI personalisation at its best.

Advertising: AI has already made forays into the world of advertising with a concept you might be familiar with: programmatic advertising. Although not everyone is happy with the results from machines buying digital ads, the technology can evolve to provide even better results in the future.

Analytics: If you have ever ventured into a tool like Google Analytics you have probably at one point become overwhelmed by the sheer amount of data and options. An analytics AI make part of the job easier for you, as it can be instructed to find every relevant data point that is business crucial, like the number of conversions or where the buyer’s funnel is clogged, and then suggest what to do next.

Optimisation tools: You might spend a lot of time A/B testing to find out what headline works best or what button colour does it for your audience. Why not let an AI handle this for you automatically?

Due diligence and auditing: Why is this mentioned here? As every serious organisation is expected to play it fair, you need a stamp of approval by your auditors. The audit world is now experiencing the introduction of AI to their traditional services, and this might help both you and your auditor in streamlining processes and freeing up time to work on digital experiences.

Despite its name, marketing automation is not AI, yet. Marketing automation involves you setting up automated workflows that can be triggered by the actions of your users, but every step is made by you. An AI marketing automation would consist of a range of content matched to the right users, based on what the system has perceived and integrated—and then the automatic delivery of the right content to the right person at the right time.

Also, as a useful exercise, ask yourself: What current tasks would you like to be automated?

What AI solutions exist today?

There is quite some time since artificial intelligence stopped being science fiction and started being science fact. But what systems are out there already? Here is a cursory look at the field:

Chatbot frameworks: A whole bunch of brands have taken a keen liking to chatbots—providing users fast and human-like answers in chat-form. As the AI gets smarter, you will probably have a harder time in recognising if the one you’re chatting with is a human or a software, but right now this is a time-saving technology providing fast service.

TensorFlow: Developed by the Google Brain Team, TensorFlow is an open-source software library, used for machine learning applications such as neural networks.

IBM Watson: A question-answering computer system made famous in 2011 when it won Jeopardy! against seasoned champions. Today, it is used as an advisor to health personnel, amongst other things.

Amazon AI: Amazon dabbles in AI, of course, and you can see some of their documentation on Amazon Web Services.

Skynet: Automatised weapons systems could provide a safer world and not enable conquering cyborg overlords in the guise of Arnold Schwarzenegger … OK, that was a joke. Don’t worry!

AI is here to stay and has probably only begun its journey in transforming the world to a better place for all human beings. If some of the examples in this article has piqued your interest, please investigate further to see if the technology can help you with your digital experiences.